High performers are not superheroes: bridging exclusive and inclusive talent management approaches for law firm sustainability

ABSTRACT

This paper elucidates findings in relation to bridging exclusive and inclusive approaches to talent management at law firms that could promote the revision of the up-or-out career model. We explore the competencies required for career success, and we describe high-performing lawyers and their peers’ profiles. We surveyed 358 lawyers and stakeholders of the lawyering role in 12 European and Latin American countries. The stakeholders noted that high performance in an array of competencies is necessary for a lawyer’s career success, but they still valued legal skills the most. Debunking the superhero myth, we argue that high performers have a narrow focus on legal skills as the driver for innovative solutions for clients, but lack strength in interpersonal competencies. In contrast, their peers have more adaptable mindsets and are more relational and focused on quality. Rather than challenging the up-or-out career model, which overvalues the role of high performers, we propose that the talent management exclusive approach is a good fit, and therefore promotes only a minimum of change. For talent management that ensures business sustainability, we support a more inclusive approach linked with strategic talent mapping and assessments that use several competency profiles and present several possible career paths.

Acknowledgments

The author is grateful to Saville Consulting for supporting her doctoral dissertation regarding free tool use and training. She appreciates the helpful insights from Rab McIver, Saville Consulting’s research director, on earlier drafts of this paper.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. By definition, a Sten scale is a standard ten scale used to cover a population range in fixed and equal standard deviation intervals, with fixed mean and standard deviations at 5.5 and 2, respectively (Cattell, 1965).

2. Hierarchical regression is a form of stepwise regression that evaluates the relationship between a set of independent variables and a dependent variable, controlling for the impact of a different set of variables on the dependent variable. Variables are entered into the analysis in a sequence of blocks, and the researcher controls the order of entry according to the hypotheses being examined. In this study, a set of control variables was entered in the first block, and a set of predictor variables was entered in the second block.